The rapid development of China’s textile industry has led to consumption and pollution of large volumes of water. Therefore, the textile industry has been the focus of water conservation and waste reduction in China’s 13th Five-Year Plan (2016–2020). The premise of sustainable development is to achieve decoupling of economic growth from water consumption and wastewater discharge. In this work, changes in the blue water footprint, grey water footprint, and the total water footprint of the textile industry from 2001 to 2014 were calculated. The relationship between water footprint and economic growth was then examined using the Tapio decoupling model. Furthermore, factors influencing water footprint were determined through logarithmic mean Divisia index (LMDI) method. Results show that the water footprint of China’s textile industry has strongly decoupled for five years (2003, 2006, 2008, 2011, and 2013) and weakly decoupled for four years (2005, 2007, 2009, and 2010). A decoupling trend occurred during 2001–2014, but a steady stage of decoupling had not been achieved yet. Based on the decomposition analysis, the total water footprint mainly increased along with the production scale. On the contrary, technical level is the most important factor in inhibiting the water footprint. In addition, the effect of industrial structure adjustment is relatively weak.

Urban agglomerations are not only the core areas leading economic growth but also the fronts facing severe resource and environmental challenges. This paper aimed to increase our understanding of urban eco-efficiency and its influencing factors and thus provide the scientific basis for green development. We developed a model that incorporates super-efficiency, slacks-based-measure, and global-frontier technology to calculate the total-factor eco-efficiency (TFEE) and used a spatial panel Tobit model to take into account spatial spillover effects. An empirical study was conducted utilizing a prefecture-level dataset in the Yangtze River Delta Urban Agglomeration (YRDUA) from 2003 to 2016. The main findings reveal that significant spatial differences exist in TFEE in the YRDUA: high-TFEE cities were majorly located in the coastal areas, while low-TFEE cities were mostly situated inland. Overall, TFEE shows a trend of “decline first and then rise with fluctuation”; the disparity between inland and coastal regions has expanded. Further regression analysis suggests that industrial structure, environmental regulation, and innovation were positively related to TFEE, while foreign direct investment was not conducive to the growth in TFEE. The relationship between population intensity and urban eco-efficiency is an inverted U-shaped curve. Finally, several specific policy implications were raised based on the results.

As the world’s top energy consumer and carbon emitter, China’s carbon emissions policies, including the low-carbon pilot initiative (LCPI) implemented in July 2010, have important effects on global climate change. Therefore, accurately assessing the effect of this policy has become extremely important for low-carbon development. This article analyses the impact of implementing LCPI on regional carbon emissions by using Guangdong Province as the study area, which has the largest economic scale, population size and carbon emissions amongst China’s low-carbon pilot provinces. The results suggest that for the entire 2010–2015 period, Guangdong’s carbon emissions were reduced by about 10% due to the implementation of LCPI. This policy produced a significant impact on the carbon emissions from manufacturing industries but showed minimal impact on the carbon emissions from energy production. Unlike previous researchers who relied on estimations, the authors of this work obtained unified carbon emissions data for 1997–2015 from the China Emission Accounts and Datasets and then constructed comparison groups by using the synthetic control method instead of performing a subjective selection. The authors also examined the impact of LCPI on carbon emissions from different sources. This article proposes that policy support and low-carbon action are necessary for reducing regional carbon emissions and that the policies must be constantly adjusted during their implementation. The successful experiences in low-carbon pilots are also worth exploring and promoting in other regions.

Unprecedented economic achievement in China’s textile industry (TI) has occurred along with rising water consumption. The goal of industrial sustainable development requires the decoupling of economic growth from resource consumption. This paper examines the relationship between water consumption and economic growth, and the internal influence mechanism of China’s TI and its three sub-sectors: the manufacture of textiles (MT) sector, the Manufacture of Textile Wearing Apparel, Footwear, and Caps (MTWA) sector, and the manufacture of chemical fibers (MCF) sector. A decoupling analysis was performed and the Laspeyres decomposition method was applied to the period from 2001 to 2014. We showed that six of the fourteen years analyzed (2003, 2006, 2008, 2009, 2011, and 2013) exhibited a strong decoupling effect and three of the fourteen years (2005, 2007, and 2010) exhibited a weak decoupling effect. Overall, China’s TI experienced a good decoupling between economic growth and water consumption from 2002 to 2014. For the three sub-sectors, the MTWA sector experienced a more significant positive decoupling than the MT and MCF sectors. The decomposition results confirm that the industrial scale factor is the most important driving force of China’s TI water consumption increase, while the water efficiency factor is the most important inhibiting force. The industrial structure adjustment does not significantly affect water consumption. The industrial scale and water use efficiency factors are also the main determinants of change in water consumption for the three sub-sectors.

The rapid development of China’s textile industry (TI) has led to severe water environmental stress. Water environmental stress of China’s TI mainly comes from large quantities of discharged wastewater and chemical oxygen demand (COD). The sustainable development of the TI is realized to achieve the decoupling between economic growth and water environmental stress. This study analyzes the decoupling elasticity results from wastewater discharge and COD discharge, respectively. Decoupling results show that TI’s wastewater has strong decoupling from economic growth for three years (2002, 2013–2014) while COD has strong decoupling for six years (2002–2003, 2008, 2010, 2013–2014). The paper further calculates the decoupling elasticity results of the TI’s three sub-sectors (manufacture of textile sector, manufacture of textile wearing and apparel sector, and manufacture of chemical fibers (MCF) sector), and calculates the factors that affect wastewater discharge. The decrement and rebound effects of wastewater discharge are analyzed based on calculated results. Decomposition results show that the scale factor is the most significant contributor to wastewater discharge, the intensity factor inhibits wastewater discharge, and the effect of the structure factor is not evident. The decrement effect of TI increases yearly, but the rebound effect shows that the absolute amount of wastewater discharge also increases. The rebound effect has declined since 2012. In the three sub-sectors, MCF’s decrement effect is the strongest, and its rebound effect is the weakest, which indicate that MCF is the biggest contributor to the discharge reduction of China’s TI.

Studying the impact of land urbanization on smog pollution has important guiding significance for the sustainable development of cities. This study adds the spatial effect between regions into the research framework of smog pollution control in China. On the basis of a panel dataset of 31 province-level administrative regions in China from 2000 to 2017, we investigate the impact of land urbanization on smog pollution. We construct a spatial weight matrix and use Moran’s I statistic and the spatial autoregressive panel data model. The research results show that land urbanization and smog pollution have an inverted U-shaped relationship. With the advancement of land urbanization, the area’s smog pollution first increases and then decreases. However, in general, China has not passed the inflection point and is still at a stage where increasing land urbanization rate aggravates smog pollution. Moreover, the country’s smog pollution has a significant spatial positive correlation that shows agglomeration. In that context, multiple environmental governance entities, including the government, enterprises, and the public, need to collaborate on measures to reduce smog pollution. Future urban construction in China will need to integrate solutions that address the current nexus between urbanization and smog pollution to achieve green and sustainable development.